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DBMS > Apache IoTDB vs. GeoSpock vs. Google Cloud Firestore vs. Microsoft Access vs. Postgres-XL

System Properties Comparison Apache IoTDB vs. GeoSpock vs. Google Cloud Firestore vs. Microsoft Access vs. Postgres-XL

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonPostgres-XL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkSpatial and temporal data processing engine for extreme data scaleCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelTime Series DBMSRelational DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteiotdb.apache.orggeospock.comfirebase.google.com/­products/­firestorewww.microsoft.com/­en-us/­microsoft-365/­accesswww.postgres-xl.org
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlfirebase.google.com/­docs/­firestoredeveloper.microsoft.com/­en-us/­accesswww.postgres-xl.org/­documentation
DeveloperApache Software FoundationGeoSpockGoogleMicrosoft
Initial release2018201719922014 infosince 2012, originally named StormDB
Current release1.1.0, April 20232.0, September 20191902 (16.0.11328.20222), March 201910 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoBundled with Microsoft OfficeOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, JavascriptC++C
Server operating systemsAll OS with a Java VM (>= 1.8)hostedhostedWindows infoNot a real database server, but making use of DLLsLinux
macOS
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononoyes infoXML type, but no XML query functionality
Secondary indexesyestemporal, categoricalyesyesyes
SQL infoSupport of SQLSQL-like query languageANSI SQL for query only (using Presto)noyes infobut not compliant to any SQL standardyes infodistributed, parallel query execution
APIs and other access methodsJDBC
Native API
JDBCAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesnoyes, Firebase Rules & Cloud Functionsyes infosince Access 2010 using the ACE-engineuser defined functions
Triggersyesnoyes, with Cloud Functionsyes infosince Access 2010 using the ACE-engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Automatic shardingShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoUsing Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACID infobut no files for transaction loggingACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesAccess rights for users can be defined per tableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.no infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard

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More resources
Apache IoTDBGeoSpockGoogle Cloud FirestoreMicrosoft AccessPostgres-XL
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